MOSAiCS-HMM: A model-based approach for detecting regions of histone modifications from ChIP-seq data
نویسندگان
چکیده
Chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq) experiments are routinely utilized for studying epigenomics of transcriptional regulation. We review some of the important statistical issues in the analysis of these experiments and extend our previous model for the analysis of ChIP-seq data of transcription factors, named MOSAiCS, with a hidden Markov model architecture (MOSAiCS-HMM). MOSAiCS-HMM provides a model-based approach for modeling read counts in histone modification ChIP-seq experiments and accounts for the spatial dependence in their ChIP-seq profiles. In addition, its R package implementation provides many functionality for summarizing these data and generating files that can be directly uploaded to the UCSC genome browser.
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